code: def test_make_mock_estimator_with_kwargs(
      estimator_class, estimator_kwargs
  ):
      """Test that make_mock_estimator behaves like the passed estimator."""
      mock_estimator = make_mock_estimator(estimator_class)
      mock_estimator_instance = mock_estimator(estimator_kwargs)
      estimator_instance = estimator_class(**estimator_kwargs)
      mock_estimator_instance.fit(y_series)
      estimator_instance.fit(y_series)
  
      assert_series_equal(
          estimator_instance.predict(fh=[1, 2, 3]),
          mock_estimator_instance.predict(fh=[1, 2, 3]),
      )
      assert (
          (
              mock_estimator_instance.strategy
              == estimator_kwargs["strategy"]
          )
          and (mock_estimator_instance.sp == estimator_kwargs["sp"])
          and (
              mock_estimator_instance.window_length
              == estimator_kwargs["window_length"]
          )
      )
  
file_path: sktime/sktime/utils/estimators/tests/test_base.py
imports: import pytest
  from pandas.testing import assert_series_equal
  from sktime.classification.base import BaseClassifier
  from sktime.clustering.base import BaseClusterer
  from sktime.datasets import load_airline
  from sktime.forecasting.base import BaseForecaster
  from sktime.forecasting.naive import NaiveForecaster
  from sktime.transformations.base import BaseTransformer
  from sktime.transformations.series.boxcox import BoxCoxTransformer
  from sktime.utils.estimators import make_mock_estimator
  from sktime.utils.estimators._base import _method_logger, _MockEstimatorMixin
label_desc: Use image node_id 7 for calling a global function with example usage: test_make_mock_estimator_with_kwargs(estimator_class, estimator_kwargs) without return types